library(plotly)
library(dplyr)
library(formattable)

# Load data
measles <- read.csv("MeaslesCases_5_30_2019.csv")
head(measles, 3)

  Year Cases Months
1 2010    63     12
2 2011   220     12
3 2012    55     12

measles$Monthly <- measles$Cases / measles$Months
graphTitle <- paste0("US Measles Cases<br>",
                     "<span style=\"font-size: 85%;",
                     "color: #144e75\">",
                     "** Up to May 30, 2019</span>")

# Create bar graph
p <- plot_ly(data = measles,
             x = ~Year,
             y = ~Cases,
             type = 'bar',
             name = 'Year Cases') %>%
    add_trace(y = ~Monthly,
              name = 'Monthly Cases') %>%
    add_lines(y = ~median(Cases),
              x = ~c(min(Year)-.5, Year, max(Year)+.5),
              line = list(color = '#144E75',
                          dash = 'dash',
                          width = 2),
              name = "Year Median") %>% 
    add_lines(y = ~median(Monthly),
              x = ~c(min(Year)-.5, Year, max(Year)+.5),
              line = list(color = '#144E75',
                          dash = 'dot',
                          width = 2),
              name = "Monthly Median") %>% 
    layout(title = list(text = graphTitle,
           font = list(size=20)),
           margin = list(l = 10, r = 10, b = 50, t = 110, pad = 4),
           yaxis = list(title = 'Cases Count'),
           xaxis = list(tickangle = 45),
           barmode = 'group')

Data extracted from the CDC Website.

• Up to May 30, the monthly rate of Measles cases during 2019 is 196.2. That's 1255.7% the last 10 years monthly median.

• With only five month of data, 2019's up to date cases are 981. That's 523.20% the last 10 years median for hole years.

• We have an Outbreak.

Thanks.